Search form

Artificial Intelligence & Machine Learning

Artificial Intelligence & Machine Learning

The last decade has seen rapid progress in the field of machine learning and neural networking. Using these techniques, computers now routinely recognise images, parse and respond to human speech, answer questions and make decisions. Welcome to the early robot future. We have increasingly sophisticated "narrow" artificial intelligences, but only the first beginnings of systems that think in open ended and general ways like we do.

There is a wide range of views about how urgent or profound the policy questions raised by general, "human level", artificial intelligence may be. But regardless of whether you think general purpose AI is imminent or still in the distant future, there are some topics raised by the state of the art in neural networking and machine learning algorithms that need to be addressed in the short term. For instance:

What rules, if any, should constrain the use of machine learning methods when coupled to the large scale surveillance technologies operated by intelligence agencies? What about the large datasets collected by private tech companies?

When algorithms, including AI and machine learning systems, make decisions that affect human lives, from the mundane (e.g. price discrimination) to the profound (e.g. sentencing recommendations), what standards of transparency, openness and accountability should apply to those decisions? If the decisions are "wrong", who is legally and ethically responsible?

How do we prevent machine learning systems from producing racially biased results, or from engaging in other problematic forms of "profiling"?

EFF is tracking these issues, and will intervene to ensure there are protections against the privacy, safety and due process problems that could be caused by poorly designed or deployed machine learning systems, while protecting the rights of innovators to build, experiment with and deploy awesome new forms of AI.

Yesterday and today, Mark Zuckerberg finallytestified before the Senate and House, facing Congress for the first time to discuss data privacy in the wake of the Cambridge Analytica scandal. As we predicted, Congress didn’t stick to Cambridge Analytica. Congress also grilled Zuckerberg on content moderation—i.e., ...

Thousands of Google staff have been speaking out against the company’s work for “Project Maven,” according to a New York Times report this week. The program is a U.S. Department of Defense (DoD) initiative to deploy machine learning for military purposes. There was a small amount of public...

Incident response standards, data sharing, and not blaming humans unfairly for the failures of machinesMore than a week after an Uber vehicle driving in autonomous mode killed a pedestrian in Tempe, Arizona — the first pedestrian death by a self-driving car — we still don’t know what exactly went wrong...

In the coming decades, artificial intelligence (AI) and machine learning technologies are going to transform many aspects of our world. Much of this change will be positive; the potential for benefits in areas as diverse as health, transportation and urban planning, art, science, and cross-cultural understanding are enormous. We've already...

Video editing technology hit a milestone this month. The new tech is being used to make porn. With easy-to-use software, pretty much anyone can seamlessly take the face of one real person (like a celebrity) and splice it onto the body of another (like a porn star), creating videos that...